Modern Factor Analytic Techniques

Morin, Alexandre J. S.; Myers, Nicholas D.; Lee, Seungmin

doi:10.1002/9781119568124.ch51

Cited by 186 publications

(169 citation statements)

References 97 publications

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“…Analyses of data should not only be based on fit indices. Close inspection of parameter estimates (e.g., factor loadings, cross-loadings) may also reveal relevant information about the model (Morin et al, 2020).…”

Section: Resultsmentioning

confidence: 99%

Validation of the French Version of the Fear of COVID-19 Scale and Its Associations with Depression, Anxiety, and Differential Emotions

Mailliez

Griffiths

Carré

2021

Int J Ment Health Addiction

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The COVID-19 crisis represents a global health concern, including mental health. Regarding the necessity to assess anxiety related to COVID-19, a scale was developed (Ahorsu et al., 2020). The goal of the present study was to validate the Fear of COVID-19 Scale in French (official language in 29 countries), and investigate its relationship with indicators of affective disturbances. The sample comprised 316 participants (271 females) recruited online during the French lockdown. They were from several regions of France. The FCV-19S underwent a forward-backward translation procedure. Its psychometric properties were evaluated with the confirmatory factor analysis (CFA). The French FCV-19S demonstrated a stable unidimensional structure with robust psychometric properties (strong internal consistency, good convergent and divergent validity, and good test-retest validity). With its robust psychometric properties in assessing the unidimensional construct of the fear of COVID-19, this scale will help to provide a better understanding of the relationship between emotions and psychological or psychiatric disorders during the pandemics in Frenchspeaking countries.

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Section: Resultsmentioning

confidence: 99%

Validation of the French Version of the Fear of COVID-19 Scale and Its Associations with Depression, Anxiety, and Differential Emotions

Mailliez

Griffiths

Carré

2021

Int J Ment Health Addiction

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“…Third, perceived parental behaviors were modeled using a four‐factor CFA model representing paternal care, maternal care, paternal neglect, and maternal neglect. In this model, a priori CUs were included to account for the methodological artifact associated with the parallel wording of the items measuring paternal and maternal behaviors (Morin, Myers, & Lee, 2020). Neglect was measured using two items, creating a locally underidentified factor (even though the model remains globally identified).…”

Section: Analysesmentioning

confidence: 99%

Longitudinal Trajectories, Social and Individual Antecedents, and Outcomes of Problematic Internet Use Among Late Adolescents

Tóth‐Király¹,

Morin²,

Hietajärvi

et al. 2021

Child Development

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Given the detrimental effects associated with problematic internet use (PIU) and the need to better understand its nature and evolution, the present study examined the development of PIU in a sample of 1,750 adolescents (aged 16–19) from Finland over a 3‐year period. We documented the social (loneliness, perceived maternal and paternal behaviors) and individual (sex) antecedents, as well as the outcome implications (depressive symptoms, substance use, academic achievement) of PIU trajectories. Outcomes also predicted PIU trajectories. Latent curve modeling revealed an initially moderate, and subsequently decreasing trajectory of PIU. PIU was predicted by loneliness, paternal neglect, maternal care, depressive symptoms, and being male. In turn, PIU trajectories predicted increases in depressive symptoms and substance use, but decreases in academic achievement.

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“…If the length of the survey is about 10 questions or fewer, it can lead to a higher completion rate and increase the likelihood that people will choose to take more of the researcher's surveys in the future. More recent studies of factor analysis do not include the VTF ratio 10:1 in their investigations [5,12,[14][15][16][17], nor the way this number is relative to the sample size or the communality magnitude when factor analysis is conducted.…”

Section: Imentioning

confidence: 99%

“…In FA, the observed indicator variables can be viewed as representing a sample of potential variables, all of which measure the same construct or factor [1,14,16,17]. Authors in [18] examined the magnitude of the correlation between the observed variables and the factor components by manipulating sample size, number of variables, number of components, and component saturation.…”

Section: A Observed Variablesmentioning

confidence: 99%

Stability of the Data-Model Fit over Increasing Levels of Factorial Invariance for Different Features of Design in Factor Analysis

Almaleki

2021

Eng. Technol. Appl. Sci. Res.

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The aim of this study is to provide an empirical evaluation of the influence of different aspects of design in the context of factor analysis in terms of model stability. The overall model stability of factor solutions was evaluated by the examination of the order for testing three levels of Measurement Invariance (MIV) starting with configural invariance (model 0). Model testing was evaluated by the Chi-square difference test (Δx2) between two groups, and Root Mean Square Error of Approximation (RMSEA), Comparative Fit Index (CFI), and Tucker-Lewis Index (TLI). Factorial invariance results revealed that the stability of the models was varying over increasing levels of measurement as a function of Variable-To-Factor (VTF) ratio, Subject-To-Variable (STV) ratio, and their interactions. There were invariant factor loadings and invariant intercepts among the groups indicating that measurement invariance was achieved. For VTF ratios 4:1, 7:1, and 10:1, the models started to show stability over the levels of measurement when the STV ratio was 4:1. Yet, the frequency of stability models over 1000 replications increased (from 77% to 91%) as the STV ratio increased. The models showed more stability at or above 32:1 STV.

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Modern Factor Analytic Techniques

Cited by 186 publications

References 97 publications

Validation of the French Version of the Fear of COVID-19 Scale and Its Associations with Depression, Anxiety, and Differential Emotions

Validation of the French Version of the Fear of COVID-19 Scale and Its Associations with Depression, Anxiety, and Differential Emotions

Longitudinal Trajectories, Social and Individual Antecedents, and Outcomes of Problematic Internet Use Among Late Adolescents

Stability of the Data-Model Fit over Increasing Levels of Factorial Invariance for Different Features of Design in Factor Analysis

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